Skilled teams that create and check your AI training data.

Four areas: image and video training data (editing, illustration, captions and preference ratings), model evaluation and RLHF, expert STEM reasoning data, and dataset QA and annotation. Coding, agent and red-teaming work is available on request.

Credential-verified specialists (PhDs, practising engineers, and domain professionals) recruited against your project's subject matter, then put through task-specific onboarding and calibration rounds before they touch production data.

Multi-pass review with inter-annotator agreement tracking, rubrics calibrated against gold answers, and QA reporting that documents error taxonomies rather than just a pass rate. You get the failure modes, not only the score. For grading and RL tasks we also run an adversarial pass that tries to break each rubric or grader before delivery.

Yes. Alongside the public formats in our catalog we design bespoke pipelines for specialised domains, custom schemas, and internal evaluation needs that off-the-shelf benchmarks don't cover.

We scale from small pilot batches through to multi-thousand-task datasets. A pilot is usually the right way to calibrate rubrics and confirm fit before committing to volume.

Usually within a week. We add 10–20 trained people from a network of around 100 vetted specialists, run calibration rounds on your spec, then move to volume.

Every engagement starts with a signed confidentiality agreement. Access is role-scoped and revoked at project end, data moves over encrypted channels into controlled environments with audit logging, and retention is defined per project.